Mastering Google ADK is the first deep-dive guide that shows developers—today and in the years ahead—how to design, build, and deploy production-ready AI agents with Google’s Agent Development Kit (ADK) and the latest Gemini 1.5 / 2.5 models. Written by cloud-architecture specialist Nathan Steele, this book strips away hype and teaches a proven, modular workflow that leading engineering teams are already using to automate research, customer support, data analysis, and more.
End-to-End Blueprint: Learn every stage—from local prototyping to secure cloud deployment—so your agents run reliably at scale.
Tool-First Methodology: Schema-driven tools and the AgentLoop replace brittle prompt chains, giving you deterministic, traceable results.
Multi-Agent Orchestration: Design collaborative or competitive agent teams with the A2A protocol and Agent Engine for real-world complexity.
Gemini Expertise: Practical guidance on streaming output, vision inputs, and model tuning—perfect for both Gemini beginners and power users.
Enterprise-Ready Patterns: CI/CD pipelines, observability, safety filters, auto-evaluation, and cost controls ensure you meet production SLAs.
Future-Proof Content: Covers the 2025 ADK roadmap, Java bindings, and integrations with LangChain, AutoGen, DSPy, Neo4j, and Vertex AI.
Nathan Steele is a veteran solutions architect who has helped Fortune 500 companies modernize data pipelines and deploy large-scale AI systems on Google Cloud. His workshops on agentic workflows and Gemini best practices have trained teams across five continents. In this book, Nathan distills years of hands-on experience into a pragmatic playbook any developer can follow.
Python engineers and ML practitioners who want to move beyond prompt hacking.
Cloud architects seeking a secure, observable framework for AI automation.
Product teams aiming to embed intelligent, tool-calling agents into SaaS or enterprise apps.
Consultants and tech leaders tasked with future-proofing their organization’s AI strategy.
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Paperback. Condition: new. Paperback. Mastering Google ADK is the first deep-dive guide that shows developers-today and in the years ahead-how to design, build, and deploy production-ready AI agents with Google's Agent Development Kit (ADK) and the latest Gemini 1.5 / 2.5 models. Written by cloud-architecture specialist Nathan Steele, this book strips away hype and teaches a proven, modular workflow that leading engineering teams are already using to automate research, customer support, data analysis, and more.Why This Book Stands OutEnd-to-End Blueprint: Learn every stage-from local prototyping to secure cloud deployment-so your agents run reliably at scale.Tool-First Methodology: Schema-driven tools and the AgentLoop replace brittle prompt chains, giving you deterministic, traceable results.Multi-Agent Orchestration: Design collaborative or competitive agent teams with the A2A protocol and Agent Engine for real-world complexity.Gemini Expertise: Practical guidance on streaming output, vision inputs, and model tuning-perfect for both Gemini beginners and power users.Enterprise-Ready Patterns: CI/CD pipelines, observability, safety filters, auto-evaluation, and cost controls ensure you meet production SLAs.Future-Proof Content: Covers the 2025 ADK roadmap, Java bindings, and integrations with LangChain, AutoGen, DSPy, Neo4j, and Vertex AI.Inside the BookPartKey Topics & Skills You'll Gain1 - Foundations: Core concepts, ADK vs. LangChain/AutoGen, high-value use cases2 - Environment Setup: CLI, folder structure, Gemini config, Google Cloud keys & billing3 - First Agent Build: Tool schemas, AgentLoop execution, debugging with traces4 - Multi-Agent Design: Role assignment, memory sharing, task routing, collaboration vs. competition5 - Gemini & Tools: Streaming, tool calling, vision, external APIs, cloud functions, RAG pipelines6 - Advanced Features: State management, evaluators, adapters, export & deployment7 - Agent Engine Deployments: Tracing UI, scaling sessions, secure API gateways, CI/CD8 - A2A & MCP: Secure messaging, identity, cross-agent governance9 - Real-World Recipes: Doc-parser notifier, research team, internal support agent, Neo4j graph app, custom modular assistant10 - Evaluation & Ethics: Auto-scoring, success metrics, hallucination handling, content moderation11 - Troubleshooting & Optimization: Latency, quotas, observability, anti-patterns, Gemini performance tuning12 - Looking Forward: ADK roadmap, open-source templates, fully autonomous systems, staying currentAbout the AuthorNathan Steele is a veteran solutions architect who has helped Fortune 500 companies modernize data pipelines and deploy large-scale AI systems on Google Cloud. His workshops on agentic workflows and Gemini best practices have trained teams across five continents. In this book, Nathan distills years of hands-on experience into a pragmatic playbook any developer can follow.Perfect ForPython engineers and ML practitioners who want to move beyond prompt hacking.Cloud architects seeking a secure, observable framework for AI automation.Product teams aiming to embed intelligent, tool-calling agents into SaaS or enterprise apps.Consultants and tech leaders tasked with future-proofing their organization's AI strategy. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798288593918
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Paperback. Condition: new. Paperback. Mastering Google ADK is the first deep-dive guide that shows developers-today and in the years ahead-how to design, build, and deploy production-ready AI agents with Google's Agent Development Kit (ADK) and the latest Gemini 1.5 / 2.5 models. Written by cloud-architecture specialist Nathan Steele, this book strips away hype and teaches a proven, modular workflow that leading engineering teams are already using to automate research, customer support, data analysis, and more.Why This Book Stands OutEnd-to-End Blueprint: Learn every stage-from local prototyping to secure cloud deployment-so your agents run reliably at scale.Tool-First Methodology: Schema-driven tools and the AgentLoop replace brittle prompt chains, giving you deterministic, traceable results.Multi-Agent Orchestration: Design collaborative or competitive agent teams with the A2A protocol and Agent Engine for real-world complexity.Gemini Expertise: Practical guidance on streaming output, vision inputs, and model tuning-perfect for both Gemini beginners and power users.Enterprise-Ready Patterns: CI/CD pipelines, observability, safety filters, auto-evaluation, and cost controls ensure you meet production SLAs.Future-Proof Content: Covers the 2025 ADK roadmap, Java bindings, and integrations with LangChain, AutoGen, DSPy, Neo4j, and Vertex AI.Inside the BookPartKey Topics & Skills You'll Gain1 - Foundations: Core concepts, ADK vs. LangChain/AutoGen, high-value use cases2 - Environment Setup: CLI, folder structure, Gemini config, Google Cloud keys & billing3 - First Agent Build: Tool schemas, AgentLoop execution, debugging with traces4 - Multi-Agent Design: Role assignment, memory sharing, task routing, collaboration vs. competition5 - Gemini & Tools: Streaming, tool calling, vision, external APIs, cloud functions, RAG pipelines6 - Advanced Features: State management, evaluators, adapters, export & deployment7 - Agent Engine Deployments: Tracing UI, scaling sessions, secure API gateways, CI/CD8 - A2A & MCP: Secure messaging, identity, cross-agent governance9 - Real-World Recipes: Doc-parser notifier, research team, internal support agent, Neo4j graph app, custom modular assistant10 - Evaluation & Ethics: Auto-scoring, success metrics, hallucination handling, content moderation11 - Troubleshooting & Optimization: Latency, quotas, observability, anti-patterns, Gemini performance tuning12 - Looking Forward: ADK roadmap, open-source templates, fully autonomous systems, staying currentAbout the AuthorNathan Steele is a veteran solutions architect who has helped Fortune 500 companies modernize data pipelines and deploy large-scale AI systems on Google Cloud. His workshops on agentic workflows and Gemini best practices have trained teams across five continents. In this book, Nathan distills years of hands-on experience into a pragmatic playbook any developer can follow.Perfect ForPython engineers and ML practitioners who want to move beyond prompt hacking.Cloud architects seeking a secure, observable framework for AI automation.Product teams aiming to embed intelligent, tool-calling agents into SaaS or enterprise apps.Consultants and tech leaders tasked with future-proofing their organization's AI strategy. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798288593918
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